1. Field of the Invention
The field of the invention generally relates to a system and method for inspecting machinery, and more particularly, to a system and method for determining whether a mechanical or an electromechanical system exhibits a defect and/or an operating characteristic during use.
2. Description of Related Art
Railroad rolling stock (locomotives, railcars, and other examples of wheeled transportation equipment for railways), gas turbines, and other types of machinery are examples of systems—assemblages of parts forming a complex or unitary whole. A system typically functions properly when its parts achieve optimal operating characteristics during use. In a mechanical or electromechanical system, one exemplary “operating characteristic” is the true temperature of a system component. If a system component overheats during use beyond a certain point, the component will break down, sometimes catastrophically. One example of this is wheel bearings for railcars, which will overheat and/or break down if the railcar wheel and/or components of a wheel bearing are defective and/or malfunction during use.
FIG. 1 illustrates an example of a conventional railcar truck 1 (sometimes referred to as a “bogie” in European parlance) that includes a wheel 4 rotatably attached to an axle 2. A wheel bearing assembly 8 is pressed onto each end of the axle 2 near the wheel plate area—typically a side surface of the wheel 4 between about the wheel's center and its rim 3. The railcar truck sideframe 6 includes a u-shaped pedestal jaw 5 that fits over a wheel bearing adapter 7, which bears down upon the wheel bearing assembly 8. Each wheel bearing assembly 8 functions to support and transfer the weight of the railroad rolling stock onto the axle 2 and through the wheel 4 to the railroad track 30. When components of each wheel bearing assembly 8 (e.g., bearings, seals, and lubricant) are in peak condition, each wheel 4 rotates with minimal friction. Otherwise, increased friction from a defective wheel 4 and/or a defective component of the wheel bearing assembly 8 can cause the wheel bearing assembly 8 to overheat and/or to break down. Various types of wheel bearing assemblies have been developed, but at present, roller bearing assemblies are common.
FIG. 2 is an end view of the conventional railcar truck 1 of FIG. 1 that further illustrates placement of the wheel bearing assembly 8 and illustrates a region (represented by vertical axis 9) of the wheel bearing assembly 8 scanned by a trackside heat sensor (not shown) (commonly referred to as a “hot box detector” within the rail industry) as the railcar truck 1 rolls past. An example of a hot box detector is shown in FIG. 3 as detector 10.
FIG. 3 is a perspective view of a conventional wayside inspection station (“WIS”) 300 configured to inspect railroad rolling stock on the fly for one or more abnormal operating characteristics, examples of which include overheated wheel bearing assemblies, dragging equipment, overheated railcar truck wheels, and the like. The WIS 300 consists of several computer-controlled detectors 10, 72, 302 that are networked with one or more local and/or remote computers (not shown). Positioned on the ground adjacent a rail of the railroad track 30, the detector 10 is a hot box detector configured to measure an operational temperature of a wheel bearing assembly of a passing railcar truck. Positioned above the ground and a predetermined distance away from the railroad track 30, the detector 72 is a hot wheel detector configured to measure an operational temperature of the railcar truck's wheel(s). Positioned on the ground between the rails of the railroad track 30, the detector 302 is a dragging equipment detector configured to detect whether the railcar truck is dragging anything. Positioned across the railroad track 30 from the hot wheel detector 72, a sight board 301 functions to align the hot wheel detector 72 and to provide a reference temperature that serves as a base value to produce semi-absolute wheel plate temperature readings.
Typically, both the hot box detector 10 and the hot wheel detector 72 are each configured to convert sensed infrared heat energy (produced by a component of a railcar truck) to an electrical signal that is proportional to the amount of heat outputted (from a wheel bearing assembly and wheel, respectively) relative to ambient temperature. The dragging equipment detector 302 is configured to convert impact energy imparted to the detector's strike plate to an electrical signal. The electrical signals (if any) outputted from each of the hot box detector 10, the hot wheel detector 72, and the dragging equipment detector 302 in response to passing railroad rolling stock are then routed to a computer processor (typically located in a trackside bungalow (not shown)) for analysis and processing.
This is further illustrated in FIG. 4, which is a diagram illustrating a conventional configuration of the WIS 300 of FIG. 3. The trackside bungalow 404 containing electrical and electronic equipment 407, 409, 410 is typically positioned near the railroad track 30. The equipment housed by the trackside bungalow 404 typically consists of a computer 410 (sometimes called a “digital processing unit”), a modem 409, and a transceiver 407, each of which may be interconnected by a wired communications channel 405. The computer 410 and the transceiver 407 are typically coupled with an external computer network (not shown) via a wireless communications channel 406 and/or an antenna 408. Additionally, the computer 410 is typically linked with one or more detectors 10, 72, 302, 402 via a wired or wireless communications channel 403 over which signals flow to and from the detectors 10, 72, 302, 402. The detectors 10, 72, and 302 were previously described above. Additionally, detector 402 is a transducer mounted to a rail of the railroad track 30 and configured to alert the WIS 300 of approaching railroad rolling stock.
It has been determined that infrared sensors (such as those typically used in hot box detectors and in hot wheel detectors) typically have a high false indication rate, since they can be affected by sun shot, and microphonics. “Sun shot” occurs when radiation from the sun reflects or directly passes into the infrared sensor and causes a flawed temperature reading. “Microphonics” describes the phenomenon where components in electronic devices transform mechanical vibrations into an undesired electrical signal (noise). As used herein, the term “false indication rate” may include two types of situations. In the first situation, a false alarm is incorrectly generated. In the second situation, a false normal reading is generated. An example of a false normal reading would include indicating that a bearing temperature was within predetermined operating limits, when in fact the bearing temperature exceeded those limits.
Studies have indicated that railcar roller bearings typically operate at a temperature that is about 40° F. (4.4° C.) above ambient in winter and at a temperature that is about 60° F. (15.6° C.) above ambient in summer. In absolute terms, the absolute operating temperatures of railcar roller bearings in hot weather may range from about 120° F. (48.9° C.) to about 160° F. (71.1° C.). Due to increased loads and different design, locomotive roller bearings typically operate about 20° F. (6.7° C.) hotter than railcar roller bearings. These studies have also shown that the operational life of railcar roller bearings decreases significantly if the roller bearings experience operational temperatures in excess of about 160° F. (71.1° C.) for long periods of time. If operating temperatures at or exceeding about 200° F. (93.3° C.) are reached, the roller bearing lubricant can oxidize and/or the bearing assembly seals can degrade. Similarly, if railcar roller bearings are continuously operated at temperatures at or below about 24° F. (−4.4° C.) the roller bearing lubricant may congeal or break down, either of which can cause the roller bearings to overheat.
In general, some governmental studies have indicated that an array of microphones can be used to identify one or more defects in railcar wheel bearing assemblies and/or wheels. These studies, however, left many long-felt needs and problems unresolved. For example, one study concluded that only about 40% of defective bearings were detected on an average train pass, and that this detection level had a 5% false indication rate. Additionally, it was determined that extraneous noise (air hose leaks, high winds, ground borne vibrations, urban sounds, etc.) and noise caused by wheel impacts with the rail(s) of the railroad track could mask the roller bearings' acoustical signatures. An array of microphones was used because conventional acoustical detection techniques would not identify all defect types if only a single microphone was used, particularly types of defects that generate low-frequency acoustic outputs. Moreover, these studies presented no solutions to the long-standing need to reduce the false indication rate.
Within the engineering/manufacturing field, multi-sensor data fusion has been contemplated to increase the accuracy with which a particularly quantity (an example of which is imbalance diagnosis of rotating machinery) can be measured. Several approaches have been proposed. Sensor-level data fusion combines data from like sensors directly and thereafter performs feature extraction and fault declaration from the fused data. Feature-level data fusion uses multiple sensors to collect a particular kind of signal. Feature extraction is then performed on the signal to obtain feature vectors, which are then fused. A fault declaration is made based on the fused feature vectors. Declaration-level data fusion requires each detector to independently produce an estimate of fault declaration. Subsequently, these estimates may be combined (using Bayesian inference methods, voting methods, and other ad hoc methods). It has also been proposed to apply feature-level data fusion to disparate data (such as displacement, acceleration, and acoustics) to capture all embedded characteristics of machine defects and enhance correctness of recognition.
Accordingly, a need exists for an inspection apparatus and method configured to reduce a false indication rate, while correctly identifying a defect or an operating characteristic in a mechanical or an electromechanical system.